The present invention relates generally to the field of data mining, and more particularly to mining medical data.
A workflow consists of a sequence of connected steps. In some workflows: (i) the steps are performed in a series order (no overlapping steps); and (ii) there is no delay or gap between consecutive steps. Other workflows are more complicated. Workflow is a depiction of a sequence of operations, declared as work of a person or group, an organization of staff, or one or more simple or complex mechanisms. Workflow may be seen as any abstraction of real work that is actually performed in the real world. For control purposes, workflow may be a view of real work in a chosen aspect, thus serving as a virtual representation of actual work. Workflows may be viewed as one fundamental building block to be combined with other parts of an organization's structure such as information silos, teams, projects, policies and hierarchies. In medical imaging, modalities are defined as any of the various types of equipment or probes used to acquire images of the body. Modalities typically do not refer to the equipment but the nature of data that is obtained from it. For example, it is possible for magnetic resonance imaging (MRI) equipment to generate multiple modalities of data. In the case of medical imaging, modalities respectively correspond to various types of diagnostic images. More specifically, in case of echocardiogram images, there are multiple types of modalities that are generated by the same physical equipment as will be further identified, below.
Disease prediction is currently done by carrying out detailed analysis of various medical exams and tests. These exams and tests are computationally expensive, time consuming, and may not account for the exam in a holistic manner.
Sixty years since its invention, echocardiography remains a critical tool in the hands of cardiologists for the diagnosis and treatment of a multitude of cardiac diseases. Echocardiography is widely used for reasons including the following: (i) relatively noninvasive nature; (ii) ease of use; (iii) associated low costs; (iv) the array of useful clinical information about the heart structure; and (v) provides blood flow and motion information.
Echocardiography examines the heart with ultrasound waves. Using the core technology of capturing reflected ultrasound, detailed 2D (two dimensional) or 3D (three dimensional) images of the heart, as well as the characterization of blood flow (Doppler), are being constructed. In the course of an exam, an expert sonographer typically: (i) switches among various modalities (3D Video, 2D Video, M-mode (time-motion mode), CW (continuous wave)-Doppler, PW (pulse wave)-Doppler and their hybrids); (ii) systematically examines the heart walls, valves and blood flow from various viewpoints; and (iii) makes and records critical measurements.
The American College of Cardiology, the American Heart Association, and the American Society of Echocardiography, among others, have provided detailed guidelines and protocols in this regard. In addition to the prior knowledge about the patient and these guidelines, findings during the course of an exam also guide a sonographer as he decides on what modality to look at next. Typical modalities encountered in an echocardiogram are: (i) 2D Video (used to study heart structure); (ii) CW Doppler (used to study blood flow through the heart valves); (iii) PW Doppler (used to study blood flow in a localized region); (iv) Color Doppler (used to study blood flow in the context of the heart structure); (v) M Mode (used to study local structure movements over time); and (vi) Text (used to record or lookup measurements).
A radiologist or cardiologist typically examines the echocardiogram, as constructed by the sonographer, for the final diagnosis. This examination can be arduous and expensive. A typical echocardiogram can generate up to 3000 image frames and text. Some automatic intelligent summarization of such exams has been attempted, but these do not provide any diagnostic insight to the doctors. Conventional workflow analysis is largely focused on identifying deviation from a standard workflow or discovering a workflow from a collection of noisy and incomplete activity logs. In the medical field, given the high costs and complexity, there has been an increased focus in the policy sphere to standardize workflow and automatically record workflow operations for applications like auditing. There have also been some attempts to automatically analyze workflows to standardize processes like surgeries, and use them for teaching. Automatic mining of workflows, from radiology departments in particular, has been used to assess recorded data quality and deviations from standard workflows.